An insurer's perspective on error and loss in pathology

David B Troxel1

  • 1School of Public Health, Health and Medical Sciences, University of California, Berkeley, California, USA. dtroxel@thedoctors.com

Abstract

Insights

Pathology malpractice claims are rare but severe, with melanoma misdiagnosis being the most frequent cause. These errors often involve delayed cancer diagnosis, impacting patient treatment and outcomes.

Area of Science:

  • Surgical Pathology
  • Medical Malpractice Law
  • Diagnostic Errors

Background:

  • Surgical pathology plays a critical role in patient diagnosis and treatment.
  • Malpractice claims can arise from errors in pathology practice, impacting patient care and healthcare systems.

Purpose of the Study:

  • To identify common errors in surgical pathology leading to malpractice claims.
  • To determine the frequency and severity of these claims.
  • To discuss the implications of pathology malpractice claims.

Main Methods:

  • Analysis of 335 pathology malpractice claims reported between 1998 and 2003.
  • Exclusion of nuisance and autopsy-related claims.
  • Categorization and frequency analysis of claim types and diagnostic errors.

Main Results:

  • Pathology malpractice claims are infrequent but carry high severity.
  • Melanoma misdiagnosis and false-negative Papanicolaou tests are particularly severe claim types.
  • Top claim categories include breast specimens, melanoma, Papanicolaou smears, gynecologic specimens, and operational errors.
  • Failure to diagnose cancer accounted for 63% of claims, leading to delayed diagnosis or incorrect treatment.

Conclusions:

  • False-negative melanoma diagnosis is the leading cause of malpractice claims against pathologists.
  • Approximately one-third of misdiagnoses involve melanoma being incorrectly identified as other benign or atypical lesions.
  • Addressing diagnostic errors in melanoma and Papanicolaou testing is crucial for reducing malpractice claims.

Related Concept Videos

Systematic Error: Methodological and Sampling Errors01:15

Systematic Error: Methodological and Sampling Errors

In the case of systematic errors, the sources can be identified, and the errors can be subsequently minimized by addressing these sources. According to the source, systematic errors can be divided into sampling, instrumental, methodological, and personal errors.
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...
Errors occurring during blood pressure monitoring01:25

Errors occurring during blood pressure monitoring

Blood pressure monitoring is a crucial clinical procedure in diagnosing and managing various cardiovascular conditions. Despite its significance, the accuracy of blood pressure measurements can be compromised by multiple factors, potentially leading to either falsely high or low readings. These inaccuracies are critical as they can significantly impact patient care. So, it is vital to understand these challenges deeply and adopt strategic approaches to minimize errors.
Several factors...
Types of Errors: Detection and Minimization01:12

Types of Errors: Detection and Minimization

Error is the deviation of the obtained result from the true, expected value or the estimated central value. Errors are expressed in absolute or relative terms.
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...
Accuracy and Errors in Hypothesis Testing01:13

Accuracy and Errors in Hypothesis Testing

Hypothesis testing is a fundamental statistical tool that begins with the assumption that the null hypothesis H0 is true. During this process, two types of errors can occur: Type I and Type II. A Type I error refers to the incorrect rejection of a true null hypothesis, while a Type II error involves the failure to reject a false null hypothesis.
In hypothesis testing, the probability of making a Type I error, denoted as α, is commonly set at 0.05. This significance level indicates a 5% chance...
Introduction to Language of Pathophysiology ll01:17

Introduction to Language of Pathophysiology ll

This lesson explores key terms that describe how diseases progress, their outcomes, and their distribution in populations.Diagnostic tests identify diseases and monitor treatment. These include blood and urine tests, biopsies, imaging (X-ray, MRI), and detection of infectious agents.Remission is a reduction or disappearance of symptoms.Exacerbation refers to the worsening of symptoms, such as increased wheezing during an asthma attack.A precipitating factor triggers an acute episode, while a...
Documentation of Nursing Diagnosis01:10

Documentation of Nursing Diagnosis

The nurse documents nursing diagnoses and enters them into the patient record. The identified patient's nursing diagnosis is either written out with a plan of care or entered into the electronic health record.
In some settings, data-driven computerized decision support systems are in place, allowing for more accurate nursing diagnoses. The database within one of these systems includes diagnostic labels defining characteristics, activities, and indicators for nursing. A nurse enters assessment...